Napping and heart rate variability in elite athletes

Sleep and autonomic nervous system (ANS) influence each other in a bidirectional fashion. Importantly, it has been proposed that sleep has a beneficial regulatory influence over cardiovascular activity, which is mostly controlled by autonomic regulation through the activity of sympathetic and parasympathetic pathways of the ANS. A well-established method to non-invasively assess cardiac autonomic activity is heart rate variability (HRV) analysis. We aimed to investigate the effect of a 40-min nap opportunity on HRV. Twelve professional basketball players randomly accomplished two conditions: 40-min nap (NAP) and control (CON). Nocturnal sleep and naps were monitored by actigraphic recording and sleep diaries. Total sleep time (TST), time in bed (TIB), sleep efficiency (SE), sleep onset latency (SOL), and wake after sleep onset (WASO) were analyzed. HRV was analyzed in 5-min segments during quiet wake before and after each condition with controlled breathing. Were analysed high (HF) and low frequency (LF) bands, the standard deviation of NN interval (SDNN), HRV index and stress index (SI). Wellness Hooper index and Epworth Sleepiness Scale (ESS) were assessed before and after both conditions. There was no significant difference in TIB, TST, SE, WASO, and VAS between NAP and CON. A significant increase in SDNN, HRV index, and LF and a significant decrease in HF, SI, ESS, and Hooper’s stress and fatigue scores were observed from pre- to post-nap. In conclusion, napping reduces sleepiness, stress and fatigue, and might provide an advantage by preparing the body for a much-required sympathetic comeback following peaceful rest.

informed about the study information, and written informed consent was obtained from each participant before the study.Athletes are classified as successful elite (eliteness' mean score = 9.0 ± 1.2), based on Swann et al. [41]' categories.Eight out of the twelve players have taken part in international tournaments and represented their country in international competitions.Seven of them have more than 8 years of experience at the highest level of competition.Players were part of the same team and they trained regularly 6-8 times per week and played 1-2 competitions per week since they signed a professional contract (i.e., 8 ± 5 years).They were asked to stay away from tobacco, alcoholic, or caffeinated beverages.None was habitual napper or presented an extreme morning or extreme evening type (Morningness-Eveningness Questionnaire's mean score = 56 ± 3.1) [42].The protocol of the present study was approved by the local Institutional Review Board (CPP SUD N° 0339/2021) and carried out according to the guidelines of the Helsinki Declaration for human experimentation.The sample size was a priori calculated using the G*power software [43], as strongly recommended [44], and based on an earlier study with a similar paradigm [45].Statistical analysis indicated a minimum required sample size of twelve participants.

Procedure
To minimize the learning effects during the study, participants were familiarized with the experimenters, sleeping room, tests, and questionnaires during a familiarization session.In addition, to assess their maximal heart rate (HR max ), players carried out a Yo-Yo Intermittent Recovery test level-1; which is considered a valid basketball-specific test for the assessment of aerobic fitness [46].The test consisted of 20-m shuttle runs performed at increasing velocities with 10-s active recovery between runs until exhaustion.
In experimental sessions, each participant completed randomly two test sessions, 72 hours apart.All sessions were performed after a reference night.Athletes had a standardized morning in the laboratory.They subjectively rated their last night's sleep, ate a standardized breakfast (8:00 h) then stayed awake doing passive activities (e.g., watching television, reading).After eating an isocaloric lunch at 12:00 p.m., they were assigned to experience nap (NAP) and nonap (CON) conditions.HRV was analyzed in 5-min segments during a quiet wake before and after each condition with controlled breathing in a supine position.
In NAP condition, participants entered the comfortably warm, fully dark, and quiet sleeping room at 12:50 h.After 10 min of acclimatization in bed, nap opportunity started at 13:00 h and lasted for 40 min.The visual analogue scale (VAS) was presented to participant following the nap opportunity to evaluate their subjective sleep quality.In the CON condition, participants spent the same amount of time seated in comfortable chairs watching television.
of the autonomic nervous system.Analysis of HRV permits insight into this control mechanism [16,17].
Moreover, HRV represents a psychophysiological marker of mental and physical well-being [18][19][20].Increased HRV reflects a healthy ANS that can respond to changing environmental circumstances [19,21].By contrast, decreased HRV is a marker of autonomic inflexibility [22] and has been linked to a very large number of physical [23,24] and psychological [25,26] diseases.Furthermore, several studies have shown that acute [27,28] and chronic [29,30] stresses lead to a decrease in HRV.In the area of sports, HRV has increasingly been used to examine training load and recovery state after training [31], to monitor changes in physical performance and individual adaptation to training [32], to assess ventilatory thresholds [33], etc… Fundamentally, HRV consists of measuring the inter-beat time intervals between consecutive heartbeats and represents the variability of intervals between consecutive R-peaks (RR) on the QRS complex on the ECG [17].HRV measures can be divided mainly into time domain measures, based on arithmetic calculations of RR intervals; and frequency domain measures, based on spectral analysis (see Malik et al. [34] for more information on methods of HRV analysis).Studies investigating the effect of daytime napping on HRV in healthy young individuals reported a reduction in cardiovascular output and a shift from sympathetic to parasympathetic (vagal) dominance from wakefulness into sleep [14,35,36].Importantly, these circadian-and sleep-dependent shifts in the ANS are critical to the maintenance of autonomic balance between parasympathetic and sympathetic branches and are beneficial for health and cognition [37,38].Moreover, Suppiah et al. [39] reported that nap did not elicit any performance or physiological benefits as monitored by HRV among adolescents.Another study aimed to explore the relationship between HRV and napping duration and their impact on handball performance [40].Although no significant difference was reported between the two nap opportunities (i.e., 20 and 60 min) on HRV, a significant correlation was showed only with long nap between HRV parameters and handball performance.
Given the pressing need to understand the role of napping on physiological and psychological health and the lack of studies investigating the effect of daytime sleep on HRV in athlete populations, the present study aimed to assess cardiac autonomic activitythrough HRV analysis -before and following an afternoon nap in elite basketball players.We hypothesize that diurnal napping would (i) change the HRV profile of athletes following nap in order to prepare them for physical stress, and (ii) impact positively perceived variables including stress, sleepiness and fatigue.

Participants
Twelve high-level professional male basketball players ( 26

Measured Variables Actigraphy and sleep diaries
Participants wore GT3X activity monitors (Actigraph, Pensacola, FL, USA) on their non-dominant arms the night before each experimental day (from 18:00 h) and took them off after the napping opportunities (at 15:00 h).Sleep parameters (TST, time in bed (TIB), sleep efficiency (SE), sleep onset latency (SOL), and wake after sleep onset (WASO)) were derived and analyzed using Actilife 6 (version 6.13.7) software.Actigraphy is a non-invasive device and was evaluated as a valid tool to assess sleep and wake behavioursbehaviours compared to the gold standard polysomnography [47].

Subjective sleep quality
The subjective sleep quality was evaluated using the visual analogueanalogue scale (VAS) [48].The VAS is a 10-cm scale that shows "Very bad sleep quality" (left side) and "Very good sleep quality" (right side).

Heart rate (HR)
Heart rate was assessed using HR monitor chest belts (Team System 2, Polar, Kempele, Finland) provided with internal memory and recorded at 1-second intervals.The HR beats were exported and analyzed using Excel software (Microsoft Corporation, Redmond, WA, USA).HR data were expressed as mean (HR mean ), peak (HR peak ), and percentage of each subject's individual HR max (%HR max ).

Heart rate variability (HRV) analysis
R-wave peaks were detected automatically by Kubios HRV Analysis Software 2.2 (Matlab, Kuopio, Finland), visually examined, and edited for artefacts [49].The same software was employed to perform the HRV analysis of the R-wave series according to the Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology guidelines [34].Kubios HRV is a cutting-edge and simple-to-use freeware for coronary heart rate variability (HRV) analysis.It comprises an improvised QRS detection algorithm and tools for noise correction, trend removal, and analysis sample selection [50].The two major components of the frequency domain, i.e., high frequency (HF, 0.15-0.4Hz) and low frequency (LF, 0.04-0.15Hz) bands, and for the time domain, the standard deviation of the NN interval (SDNN), an index of global variability, were analyzed.Moreover, HRV triangular index (HRV index) and stress index (SI) were also calculated.HRV index is a geometric measure that calculates the integral of the density of the RR interval histogram divided by its height and reflects the global HRV.A 5-min epoch is conventionally used to study the above-mentioned variables [51].Normalized HRV values (LF nu, HF nu) were calculated from the raw values of either short-term frequency band (LF or HF) divided by the total spectral power (typically LF + HF), with the value of this expressed as a decimal [52].Unlike raw power, normalized units allow direct comparison between frequency and autoregressive methods for calculating spectral power, between spectral power expressed as ms 2 or bpm 2 , and between different algorithms for calculation.

Hooper scale
This is a validated psychological self-reporting scale of sleep quality, fatigue, stress, and muscle pain.Parameters were measured separately using a 7-point subjective rating scale ranging from 1 "very, very low" to 7 "very, very high".The total score indicates the athlete's form state or readiness to train [53].

Epworth Sleepiness Scale (ESS)
Daytime sleepiness was assessed using a scale of eight elements (i.e., ESS).Participants assign a score of "0" to "3" for each situation where there is "no chance" for "0", a low chance for "1", "a moderate chance" for "2" and "a high chance" for "3" to fall asleep.The score obtained from the scale ranges from "0" to "24" [54].

Statistical analysis
Analyses were performed using Excel (Microsoft Office, v.2016) and SPSS Statistics (IBM, v.23) software.All data were expressed as means ± standard error of the mean (SEM).The Shapiro-Wilk W-test revealed that the normalized units of LF (LF nu) and HF (HF nu), SDNN, HRV index, ESS and Hooper's fatigue and total score were normally distributed.Analysis was performed using a two-way repeated measures ANOVA [2 conditions (CON and NAP) x2 times (pre and post)] for HR mean , HR peak , LF nu, HF nu, SDNN, HRV index, ESS, Hooper's fatigue, and the total score.ANOVA effect sizes were calculated as partial eta squared (np2).When significant main or interaction effects were observed, pairwise comparisons were performed using the Bonferroni post-hoc test.Sleep parameters, SI and Hooper's sleep, stress, and muscle soreness scores being not normally distributed, were analyzed using Friedman nonparametric analysis of variance, and pairwise comparisons were conducted using the Wilcoxon test.

Objective and subjective sleep Parameters
Statistical analysis showed no significant difference during the night before experimental days in objective (i.e., TIB, TST, SE and WASO) and subjective (i.e., VAS) sleep parameters between the CON and NAP conditions.
Bonferroni post-hoc test revealed that HR peak was significantly higher in post-nap wakefulness compared to pre-nap wakefulness (p = 0.004) (Figure 1).

FIG. 1.
Mean values (± SEM) for HR mean and HR peak before and after NAP and CON conditions.*: significant difference (p < 0.05).Abbreviations: CON, control condition; NAP, nap condition; Pre, before nap/rest period; Post, after nap/rest period.

HRV analysis Frequency domain
Statistical results revealed a significant interaction (condition × time)  noticed a significant decrease in HF from pre-to post-nap wakefulness, accompanied by a simultaneous increase in LF.Interestingly, there were no significant changes in the CON condition.Taken together, these results suggest a sympathetic dominance following the nap opportunity.

Time-domain
Importantly, previous studies reported significant changes in HRV profile from wakefulness into sleep and across different sleep stages during nocturnal sleep [12,13] as well as daytime naps [14,15].
The limited number of studies investigating the effect of daytime napping on HRV using various experimental protocols reported a shift of the ANS from sympathetic to parasympathetic dominance from wakefulness into sleep [14,15,35,36,56].This vagal dominance is characterized by a reduced heart rate coupled with increased HF activity and a marked reduction of LF bands.Throughout the progression of non-rapid eye movement (NREM) sleep, HF activity remains elevated, with higher vagal modulation compared to rapid eye movement (REM) sleep, suggesting an overall reduction in cardiovascular output and dominance of parasympathetic/vagal activity during NREM sleep [14,15,35,36,56].Importantly, these fluctuations and dynamic changes in the autonomic profile are similar to those seen during nocturnal sleep [35], are associated with significant benefits for the cardiovascular system, and may be responsible for the homeostatic regulatory balance between sympathetic and vagal activity [12].
This balance has been correlated with reduced risk for cardiovascular disease, diabetes, and all-cause mortality [24], suggesting a cardioprotective function of sleep [12] which has led some researchers to describe normal sleep as a "cardiovascular holiday" [12].
Interestingly, only one study compared the impact of daytime napping on the ANS from pre-to post-nap wakefulness [56].The study of AlQatari et al. [56] showed an increase in LF during post-nap wakefulness compared with that during pre-nap wakefulness.The current study showed significant changes regarding HRV profile from pre-to post-nap wakefulness, including a marked increase in LF.This result is in line with the previous report [56], indicating relative sympathetic dominance.Similar to the results of AlQatari et al. [56], we noticed a significant decrease in HF, which also supports the abovementioned statement regarding the restoration of sympathetic dominance during post-nap wakefulness.Moreover, a significant increase in the LF/HF ratio has been measured after-compared to pre-nap wakefulness [56].Although the LF/HF ratio was proposed as an index describing the balance between the two branches of the ANS, in which an increased ratio reflects sympathetic dominance and a reduction in this ratio indicates parasympathetic dominance [57], this index has not been taken into account in the present study due to the several limitations described in previous research [55].According to Billman [55], the complex nature of LF power (i.e., the LF component of HRV is a reflection of fluctuations in both sympathetic and parasympathetic activity) and the non-linear interactions between sympathetic and parasympathetic nerve activity that are confounded by the mechanical effects of respiration and prevailing heart rate, make it impossible (i) to delineate the physiological basis for SDNN values increased significantly in post-nap wakefulness (p = 0.04 (Figure 3.a).
Interestingly, there were no significant changes for the CON condition (Figure 3.b).

Stress index
A significant decrease was noticed in stress index (SI) during post-nap wakefulness compared to pre-nap wakefulness (p = 0.01).Results showed no significant changes in CON condition (Figure 4).
Bonferroni post-hoc test revealed that ESS was significantly lower after nap compared to before nap (p = 0.03).In the same way, a significant decrease was observed in Hooper's post-nap stress, fatigue and total score compared to pre-nap (p = 0.009, p = 0.01, p = 0.04, respectively) (Figure 5).

DISCUSSION
In this study, we aimed to investigate the impact of daytime sleep on cardiac autonomic activity (i) to fill the gap in the literature and (ii) to give insight regarding the beneficial effect of nap reported in our previous papers [7][8][9][10].To our knowledge, this is the first study to investigate the effect of a 40-min daytime nap opportunity on HRV in elite basketball players.Our findings showed that the HRV profiles of participants changed after a daytime nap, while no significant changes were reported for the control condition.We noticed a significant increase in HR peak , SDNN, HRV index, and LF nu and a significant decrease in HF nu and SI following the nap opportunity.
Moreover, daytime napping decreased Hooper's stress, fatigue, total score, and subjective sleepiness according to ESS.
It is well established that changes in LF and HF reflect specific changes in cardiac autonomic regulation.There is wide consensus regarding the significance of the HF component, which reflects cardiac parasympathetic nerve activity [13,24,34].In contrast, the LF band was assumed to reflect a dominant sympathetic effect [17,34].It is worth mentioning that the meaning of the LF component is still debated.Some researchers consider LF as a marker of sympathetic activity, while other investigators believe that the LF component of HRV is a reflection of fluctuations in both sympathetic and parasympathetic activity [13,17,34,55].The current study showed a significant increase in HR peak and time-domain parameters of HRV (i.e., SDNN and HRV index) after NAP.In addition, we ± 5 years; 193 ± 7 cm; 87 ± 11 kg; 13 ± 2 % body fat and 17 ± 6 years expertise) volunteered to participate in the study.They were fully Biology of Sport, Vol.41 No3, 2024 215 Napping and heart rate variability in elite athletes